Abstract

Magnetic Resonance Imaging Image Analysis Using Diffusion Weighting

Author(s): Flaviana*

The brain is one of the largest organs in the human body and plays a major role in visual processing, hearing, memory, body movement control and so on. Microscopically, the human brain can be described as the random movement of water molecules within the brain tissue. By making further observations of these molecular movements, tissue boundaries within the brain can be visualized. In the field of medicine, several visual diagnostic tools are known to detect and evaluate the brain's response and function. Magnetic Resonance Imaging (MRI) is a medical imaging technique that provides important information about the soft tissue anatomy of the human body. By scanning the brain, doctors can diagnose if there are abnormalities in the brain. MRI image processing and analysis is an important part of the MRI modality, which is to improve image quality and extract information from MRI image data in an efficient and accurate manner. Diffusion-Weighted Imaging (DWI) provides significant structural information of the brain at the cellular level, emphasizing aspects of brain pathophysiology. In theory, DWI is based on the motion of water molecules so that it can describe tissue microstructure, and the opportunity to perform tumor characterization that can provide a new perspective for clinical experts in developing brain tumor treatment. The development of image processing techniques in the medical field today allows for more in-depth analysis of MRI scanning images that have been used in hospitals. This study aims to classify area groups in Diffusion Weighting (DW) MRI phase images, make statistical observations of the area groups, and evaluate the extent to which the image classification has been effectively carried out.